This is a new project, I’m working on from early last year. The motivation behind this project is to build a programing language that allows users to analyze private data without exposing sensitive information. Many data analysis languages (R, Python, MATLAB etc.) in the current market assume direct access to data. PRIVATE, on the other hand, performs a privacy calculation that will make sure only non-sensitive information is released to the user.
This is the tutorial series by Simon Dennis, Founder of PRIVATE
- The Design Of Private: A Privacy-Preserving Probabilistic Language
- An Introduction To The Private Language
- Bayesian Estimation With Private Data
- Bayesian Inference With Private Data
- Plotting In Private
Contribute to PRIVATE: Git-hub